Job Overview
This role is a core member of Bybit’s AI team, covering both LLM Application Engineering and Personalized Recommendation Systems. You will participate in the algorithm development of Bybit’s flagship AI product TradeGPT, lead end-to-end optimization of the recommendation system, and directly drive platform user growth and trading experience improvement through algorithmic capabilities.
Responsibilities
1. LLM & AI Agent Direction
- Responsible for core AI algorithm development and iteration of Bybit’s AI Agent application TradeGPT
- Integrate mainstream AI platforms (OpenAI, Anthropic, Google Gemini, open-source models, etc.) and build a unified model access layer
- Build a Prompt Engineering framework to continuously improve model output quality and stability
- Design and implement a RAG knowledge base retrieval system to support accurate Q&A and decision assistance in financial scenarios
- Participate in AI product architecture design and technology selection, driving the team’s overall AI engineering capability growth
2. Recommendation System Direction
- Responsible for recommendation system algorithm development, covering the full pipeline of recall, ranking, and re-ranking
- Build user and asset profiles, mining user trading behavior and interest features
- Focus on cutting-edge directions (LLM + recommendation, sequential recommendation, multi-objective optimization) to drive technical implementation
- Design A/B testing experiments and continuously improve recommendation performance metrics through data-driven approaches
Requirements
Basic Qualifications
- 3+ years of software engineering experience, including 1+ year of AI/ML related project experience
- Strong Python skills, familiar with mainstream AI frameworks such as LangChain and LlamaIndex
- Hands-on experience with LLM API integration (OpenAI / Claude / Gemini, etc.)
- Understanding of RAG architecture and vector databases (Pinecone, Weaviate, Qdrant, etc.)
- Familiar with machine learning fundamentals (LR, GBDT, DNN), with complete experience in feature engineering and offline training + online serving
- Good engineering practices: code quality, unit testing, CI/CD standards
Preferred Qualifications
- Experience with model fine-tuning (Fine-tuning / LoRA / RLHF)
- Familiar with MLOps toolchains (MLflow, Weights & Biases, etc.)
- Experience in Agent / Multi-agent system development
- Experience with big data processing (Spark / Hive / Flink)
- Understanding of AI safety and Responsible AI practices
- Experience with cloud platform AI services (AWS / GCP / Azure)
- Previous algorithm experience in finance, cryptocurrency, or trading scenarios is a plus